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How Social Media Reacting to Bakso Malang as Culinary Business on Post Covid 19: A Sentiment Analysis.

Authors :
Persada, Satria Fadil
Kumalasari, Riesta Devi
Shanti, Mardhatilah
Lukiyanto, Kukuh
Putri, Gabriella Sagita
Ramadhan, Chelsea Aisiyah
Young, Michael Nayat
Prasetyo, Yogi Tri
Source :
Procedia Computer Science; 2024, Vol. 234, p463-469, 7p
Publication Year :
2024

Abstract

Indonesian cuisine, especially Bakso, is one of the trendy foods that many travelers try to consume. Among the variations of Bakso, Bakso Malang is one of the most popular variants that is much talked about in social media. The present study analyzes the sentiment text mining of Bakso Malang business on post covid period from a natural language processing (NLP) social perspective. The data was taken from scraping to social media by "bakso malang" keywords. A total of 331 lexicon-filtering Tweets were gathered in the middle of March 2023. The corpus data were analyzed by valance aware dictionary and sentiment reasoner (Vader) sentiment analysis. K-means conducted the cluster of expressions. The result shows the variation of sentiments expressed in social media by anger, disgust, fear, joy, sadness, and surprise with 1.21%, 1.21%, 4.83%, 32.33%, 3.02%, and 57.40%, respectively. Many contents were discussed with keywords of "malang", "bakso", "enak", "makan", "foodfess2", "mau", and "pengen". Behavioural insight shows joy expression when discussing Bakso Malang. Further insights and recommendations are discussed in the paper. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18770509
Volume :
234
Database :
Supplemental Index
Journal :
Procedia Computer Science
Publication Type :
Academic Journal
Accession number :
176900806
Full Text :
https://doi.org/10.1016/j.procs.2024.03.028